Articles | Volume 2, issue 1
Wind Energ. Sci., 2, 295–306, 2017
https://doi.org/10.5194/wes-2-295-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Wind Energ. Sci., 2, 295–306, 2017
https://doi.org/10.5194/wes-2-295-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
02 Jun 2017
Research article
| 02 Jun 2017
Atmospheric turbulence affects wind turbine nacelle transfer functions
Clara M. St. Martin et al.
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Cited
13 citations as recorded by crossref.
- Nacelle anemometer measurement‐based extremum‐seeking wind turbine region‐2 control for improved convergence in fluctuating wind Z. Wu et al. 10.1002/we.2477
- Wind Turbine Multivariate Power Modeling Techniques for Control and Monitoring Purposes D. Astolfi et al. 10.1115/1.4048490
- Snow-powered research on utility-scale wind turbine flows J. Hong & A. Abraham 10.1007/s10409-020-00934-7
- Analysis of Wind Turbine Aging through Operation Data Calibrated by LiDAR Measurement H. Kim & J. Kim 10.3390/en14082319
- Integration of System Level CFD Simulations into the Development Process of Wind Turbine Prototypes M. Arnold et al. 10.1088/1742-6596/1618/5/052007
- Estimation of the Performance Aging of the Vestas V52 Wind Turbine through Comparative Test Case Analysis D. Astolfi et al. 10.3390/en14040915
- Evaluation of wind speed estimates in reanalyses for wind energy applications S. Brune et al. 10.5194/asr-18-115-2021
- The super-turbine wind power conversion paradox: using machine learning to reduce errors caused by Jensen's inequality T. McCandless & S. Haupt 10.5194/wes-4-343-2019
- Perspectives on SCADA Data Analysis Methods for Multivariate Wind Turbine Power Curve Modeling D. Astolfi 10.3390/machines9050100
- Multivariate SCADA Data Analysis Methods for Real-World Wind Turbine Power Curve Monitoring D. Astolfi et al. 10.3390/en14041105
- Wind Turbine Operation Curves Modelling Techniques D. Astolfi 10.3390/electronics10030269
- Multivariate Wind Turbine Power Curve Model Based on Data Clustering and Polynomial LASSO Regression D. Astolfi & R. Pandit 10.3390/app12010072
- Observing and Simulating Wind-Turbine Wakes During the Evening Transition J. Lee & J. Lundquist 10.1007/s10546-017-0257-y
12 citations as recorded by crossref.
- Nacelle anemometer measurement‐based extremum‐seeking wind turbine region‐2 control for improved convergence in fluctuating wind Z. Wu et al. 10.1002/we.2477
- Wind Turbine Multivariate Power Modeling Techniques for Control and Monitoring Purposes D. Astolfi et al. 10.1115/1.4048490
- Snow-powered research on utility-scale wind turbine flows J. Hong & A. Abraham 10.1007/s10409-020-00934-7
- Analysis of Wind Turbine Aging through Operation Data Calibrated by LiDAR Measurement H. Kim & J. Kim 10.3390/en14082319
- Integration of System Level CFD Simulations into the Development Process of Wind Turbine Prototypes M. Arnold et al. 10.1088/1742-6596/1618/5/052007
- Estimation of the Performance Aging of the Vestas V52 Wind Turbine through Comparative Test Case Analysis D. Astolfi et al. 10.3390/en14040915
- Evaluation of wind speed estimates in reanalyses for wind energy applications S. Brune et al. 10.5194/asr-18-115-2021
- The super-turbine wind power conversion paradox: using machine learning to reduce errors caused by Jensen's inequality T. McCandless & S. Haupt 10.5194/wes-4-343-2019
- Perspectives on SCADA Data Analysis Methods for Multivariate Wind Turbine Power Curve Modeling D. Astolfi 10.3390/machines9050100
- Multivariate SCADA Data Analysis Methods for Real-World Wind Turbine Power Curve Monitoring D. Astolfi et al. 10.3390/en14041105
- Wind Turbine Operation Curves Modelling Techniques D. Astolfi 10.3390/electronics10030269
- Multivariate Wind Turbine Power Curve Model Based on Data Clustering and Polynomial LASSO Regression D. Astolfi & R. Pandit 10.3390/app12010072
1 citations as recorded by crossref.
Latest update: 24 Jun 2022
Short summary
We use upwind and nacelle-based measurements from a wind turbine and investigate the influence of atmospheric stability and turbulence regimes on nacelle transfer functions (NTFs) used to correct nacelle-mounted anemometer measurements. This work shows that correcting nacelle winds using NTFs results in similar energy production estimates to those obtained using upwind tower-based wind speeds. Further, stability and turbulence metrics have been found to have an effect on NTFs below rated speed.
We use upwind and nacelle-based measurements from a wind turbine and investigate the influence...
